• Journal of Welding and Joining
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• v.13 no.4
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• pp.132-146
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• 1995

Flaw classification(determination of the flaw type) and flaw sizing (prediction of the flaw shape, orientation and sizing parameters) are very important issues in ultrasonic nondestructive evaluation of weldments. In this work, new techniques for both classification and sizing of flaws in weldments are described together with extensive review of previous works on both topics. In the area of flaw classification, a methodology is developed which can solve classification problems using probabilistic neural networks, and in the area of flaw sizing, a time-of-flight equivalent(TOFE) sizing method is presented.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.248-261
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• 1997

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1996.11a
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• pp.167-176
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• 1996

Flaw classification and sizing are very essential issues in quantitative ultrasonic nondestructive evaluation of various materials and structures including weldments. For performing of these tasks in an automated fashion, we are developing an intelligent ultrasonic evaluation system with a multi-axis portable scanner which can do consistent and efficient acquisition and processing of ultrasonic flaw signals. Here we present our efforts to develop of this intelligent system including design of the portable scanner, acquisition and processing of ultrasonic flaw signals, display of pseudo 3-D image of flaws, and classification and sizing of flaws in weldments.

• Journal of the Korean Society for Nondestructive Testing
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• v.15 no.2
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• pp.395-406
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• 1995

Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic pattern recognition technique. Here brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on probabilistic neural networks as efficient classifiers for many practical classification problems. In an example probabilistic neural networks are applied to classify flaws in weldments into 3 classes such as cracks, porosity and slag inclusions. Probabilistic nets are shown to be able to exhibit high performance of other classifiers without any training time overhead. In addition, forward selection scheme for sensitive features is addressed to enhance network performance.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.1
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• pp.11-22
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• 1997

It is very essential to get the accurate classification of defects in primary pressure vessel and piping welds for the safety of nuclear power plant. Ultrasonic testing has been widely applied to inspect primary pressure vessel and piping welds of nuclear power plants during PSI / ISI. Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic Pattern recognition technique. Here, a brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on Fuzzy-UTSCS (UT signal classification system) as efficient classifiers for many practical classification problems. As an example Fuzzy-UTSCS is applied to classify flaws in ferrite pressure vessel weldments into two types such as linear and volumetric. It is shown that Fuzzy-UTSCS is able to exhibit higher performance than other classifiers in the defect classification.

• Journal of Power System Engineering
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• v.13 no.5
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• pp.95-102
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• 2009

A steam generator (boiler) in thermal power plants, consisting of more than 30,000 parts and components, can lead to the plant shutdown with damage to even the small part of the components; esp., like weld failures on boiler tubes. Consequently it is greatly demanded to improve the quality of the weld on the boiler tube for the stable operation of the power plants. Because of the feature of the welding, which is done past by melting the work pieces and adding a filler material that cools to become a strong coalescence, there is a great possibility that weld failures take place. As a result, it is regulated to make a non-destructive testing, like radiography test, to detect defects and flaws in the weld. The current film radiography test provides a lower image quality exceeding 2.0% of a basic quality level for a penetrameter, it is very likely to fail to detect micro defect. As a result, the prevention for the boiler tube failure has not been made effectively. In this study, computed radiography technology has been applied as a digital radiography test to the boiler tube weld, and Se-75 radiation source was used to improve the image quality, instead of Ir-192 source. As a result of this study, it is proven to save the time and cost for test and to enhance the quality level of penetrameter penetrating image, which enables to upgrade the quality of radiography test to the boiler tube weld.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.70-77
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• 2008

The purpose of this study is to compare the quality of digital radiography image with that of classical film images for welded structure in power plants. The CMOS(Complementary Metal Oxide Semiconductor) flat panel detecter and Agfa D5 film are used to image flaw specimens respectively. In the test, CMOS flat panel detector has been determined to have a better image than that of film image. In the IQI(Image Quality Indicator) transmission test, one or two more line can be seen in digital image than in film image. Digital Radiography Test enabled to successfully detect all defects on the weld specimens fabricated with real reheat stem pipe and boiler tube as well. In the specific comparison test, Digital radiography test detected micro flaws in the size of 0.5 mm in length by 0.5 mm in depth. However, film test has limited it to 1.0 mm in length by 1.0 mm in depth. As a result of this study, digital radiography technology is estimated well enough to perform the inspection in the industry with far more cost effective way, compared to the classical film test.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.3
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• pp.40-47
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• 2011

KSNPs(Korea Standard Nuclear Power Plant) have been applied the break exclusion criteria to the high energy lines passing through containment penetration area to ensure that piping failures would not cause the loss of containment isolation function, and to reduce the resulting dynamic effects. Systems with the criteria are the Main Steam system, Feed Water system, Steam Generator Blowdown system, and Chemical & Volume Control system. In accordance with FSAR(Final Safety Analysis Report), a 100% volumetric examination by augmented in-service inspection of all pipe welds appled the break exclusion criteria is required for the break exclusion application piping. However, it is difficult to fully satisfy the requirements of inspection because 12", 8" and 6" weldolet weldments of Main Steam pipe line have complex structural shapes. To resolve the difficulty on the application of conventional UT(Ultrasonic Testing) technique, realistic mock-ups and UT calibration blocks were made. Simulations of conventional UT were performed utilizing CIVA, a commercial NDE(Nondestructive Examination) simulation software. Phased array UT experiments were performed through mock-up including artificial notch type flaws. A phased array UT technique is finally developed to improve the reliability of ultrasonic test at main steam line pipe to 12", 8" and 6" branch connection weld.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.4 no.2
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• pp.40-45
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• 2008

There exist many types of pipe and component fatigue through vibrations, thermal fatigues or shifting. In some cases of thermal stratification/thermal fatigue, pipes & components are receiving thermal stress by means of material expansion and shrinkage by continuous thermal repetitive variation. Small cracks initially occur on the inside surface by thermal stress. These cracks grow in depth the pipe wall and finally come to a rupture. Pipe parts of susceptibility to thermal stratification and thermal fatigue are now being examined by conventional UT(ultrasonic test) as volumetric examination. It is difficult to fully satisfy the code & standards requirements because 3" weldolet weldments of RCS 16" pipe to 3" branch connection lines have complex structural shape. To solve the problems of conventional UT examination, we made a realistic mock-up and UT calibration block. We performed a simulation of phased array UT utilizing CIVA as NDE(Non-Destructive Examination) simulation software. Also we designed phased array UT transducer and wedge, optimal frequency by using simulation data. We performed phased array UT experiment through mock-up including artificial flaws(notch). The phased array UT technique is finally developed to improve the reliability of ultrasonic test at RCS 16" pipe to 3" branch connection weld.